There are a number of potentially valuable uses of electroencephalogram (EEG) and magnetoencephalogram (MEG) traces for detecting certain brain states, such as Alzheimer's disease, and for mapping spatial patterns in structures associated with certain behaviorial activity, such as response to certain stimuli, abnormal brain activity, and psychological states and operations.
Heretofore, the potential of EEG in these areas has been limited by inability to identify brain activity signals which are related to a behavioral event of interest, due to masking of signals by clutter and noise, and lack of information about the sites of brain activity. For example, strong electromuscular potentials generated outside the surface of brain mask the presence of 40 Hz signals generated from within brain sites.
One prior art approach for enhancing EEG signal information has been to reduce noise by ensemble time averaging over several time intervals to remove random activity. This does not remove clutter components which are present in each of the averaged time intervals. A brain electrical activity mapping (BEAM) technique, described in U.S. Pat. No. 4,408,616, applies this temporal averaging approach to multisensor arrays, for purposes of brain mapping.
The problem of localizing and determining spatial distribution of brain activity has been addressed by a "software lens" approach, developed by the inventor and described in U.S. Pat. No. 4,416,288. However, spatial and temporal frequency clutter have the effect of blurring the spatial convolution, and thus have limited the power of the method heretofore.